MIT's Lab for Computational Physiology at Institute for Medical Engineering & Science (IMES) has an immediate opening for a Postdoctoral Associate in Machine Learning and Data Science for Medicine. We are seeking a highly-motivated individual to join a multidisciplinary research team to develop machine learning techniques for medicine, physiological modeling, and treatment decision support. The project offers opportunities to develop/apply novel machine learning and statistical methods to derive actionable insights from heterogeneous observational data from electronic health records, including clinical time series, medication/procedures, physician notes and reports, and physiological signals.
The ideal candidate will have demonstrated an outstanding capability for independent research in machine learning or statistical data analysis. Candidate must hold a Ph.D. degree in Computer Science, Machine Learning, Statistics, or a related field. Knowledge and experience in one or more of the following areas would be desirable: deep learning, representation learning and latent variable modeling, high-dimensional multivariate time series analysis, dynamical systems and state-space models, and reinforcement learning. Experience in machine learning for healthcare, clinical medicine, or physiological time series analysis would be preferred. Familiarity with causal inference and dynamic treatment regimes would be a plus, but not required.
Duties will include conducting original research, data assembly and analysis, assisting with writing technical manuscripts, publishing in the peer-reviewed scientific literature, train/mentor students, and collaborating on the development of research proposals.
Successful candidate will work with researchers and faculty members from MIT IMES, CSAIL, and members of the MIT-IBM Watson AI Lab. In addition to a curriculum vitae, applicants should submit a short statement of research interest to Li Lehman, lilehman<at>mit.edu
Li-wei Lehman, Ph.D. Research Scientist Laboratory for Computational Physiology Institute for Medical Engineering & Science Massachusetts Institute of Technology http://web.mit.edu/lilehman/www/